update

diff --combined report/.gitignore
index 7f35862,7f35862..9ee4f69
--- 1/report/.gitignore
--- 2/report/.gitignore
+++ b/report/.gitignore
@@@ -5,3 -5,3 +5,4 @@@
  *.pyg
  *.toc
  *.eps
++*.synctex.gz

diff --combined report/ass2-1.tex
index 4ae080f,aa53fe7..d487425
--- 1/report/ass2-1.tex
--- 2/report/ass2-1.tex
+++ b/report/ass2-1.tex
@@@ -1,38 -1,22 +1,38 @@@
 -
  \chapter{Probabilistic representation and reasoning (and burglars)}
  \section{Bayesian network and the conditional probability tables}
  \begin{figure}[H]
        \caption{Bayesian network, visual representation}
        \centering
 -      %\includegraphics[scale=0.5]{d1.eps}
 +      \includegraphics[scale=0.5]{d1.eps}
  \end{figure}
 -\strut\\
 +
 +We introduced a \textit{Noisy OR} to represent the causal independence of
 +\textit{Burglar} and \textit{Earthquake} on Alarm. Probabilities for the causes
 +of the alarm are calculated using days, in practice this means that the
 +smallest discrete time interval is one day. The calculation for the probability
 +of a burglar is then calculated with the following formula(taking leap years
 +into account and assuming a standard gregorian calendar).
 +$$\frac{1}{365 + 0.25 - 0.01 - 0.0025}=\frac{1}{365.2425}$$
 +
 +This gives the following probability distributions\\
  \begin{tabular}{|l|ll|}
        \hline
 -      & \multicolumn{2}{c|}{Radio}\\
 -      Earthquake & T & F\\
 +      & \multicolumn{2}{c|}{Earthquake}\\
        \hline
 -      T & $0.9998$ & $0.0002$\\
 -      F & $0.0002$ & $0.9998$\\
 +      T & $0.0027$ & $0.9972$ \\
 +      F & $0.9973$ & $0.0027$\\
        \hline
  \end{tabular}
  %
 +\begin{tabular}{|l|ll|}
 +      \hline
 +      & \multicolumn{2}{c|}{Burglar}\\
 +      \hline
 +      T & $0.0027$ & $0.9973$ \\
 +      F & $0.9973$ & $0.0027$\\
 +      \hline
 +\end{tabular}
 +
  \begin{tabular}{|l|ll|}
        \hline
        & \multicolumn{2}{c|}{$I_1$}\\
@@@ -42,6 -26,7 +42,6 @@@
        F & $0$ & $1$\\
        \hline
  \end{tabular}
 -%
  \begin{tabular}{|l|ll|}
        \hline
        & \multicolumn{2}{c|}{$I_2$}\\
@@@ -51,10 -36,11 +51,10 @@@
        F & $0$ & $1$\\
        \hline
  \end{tabular}
 -%
  \begin{tabular}{|ll|ll|}
        \hline
-       && \multicolumn{2}{c|}{Burglar}\\
-       i1 & i2 & T & F\\
+       && \multicolumn{2}{c|}{Alarm}\\
+       $I_1$ & $I_2$ & T & F\\
        \hline
        T & T & $1$ & $0$\\
        T & F & $1$ & $0$\\
@@@ -62,7 -48,7 +62,7 @@@
        F & F & $0$ & $1$\\
        \hline
  \end{tabular}
 -%
 +
  \begin{tabular}{|l|ll|}
        \hline
        & \multicolumn{2}{c|}{Watson}\\
@@@ -72,6 -58,7 +72,6 @@@
        F & $0.4$ & $0.6$\\
        \hline
  \end{tabular}
 -%
  \begin{tabular}{|l|ll|}
        \hline
        & \multicolumn{2}{c|}{Gibbons}\\
@@@ -80,13 -67,4 +80,13 @@@
        T & $0.99$ & $0.01$\\
        F & $0.04$ & $0.96$\\
        \hline
 -\end{tabular}
 +\end{tabular}
 +\begin{tabular}{|l|ll|}
 +      \hline
 +      & \multicolumn{2}{c|}{Radio}\\
 +      Earthquake & T & F\\
 +      \hline
 +      T & $0.9998$ & $0.0002$\\
 +      F & $0.0002$ & $0.9998$\\
 +      \hline
 +\end{tabular}